code: def forward(self, inputs):
      y = self._conv(inputs)
      y = self._batch_norm(y)
      return y
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import paddle
  from paddle import ParamAttr
  import paddle.nn
  import paddle.nn.functional
  from paddle.nn import Conv2D, BatchNorm, Linear, Dropout, PReLU
  from paddle.nn import AdaptiveAvgPool2D, MaxPool2D, AvgPool2D
  from paddle.nn.initializer import XavierNormal, Constant
  import math
label_desc: Use image node_id 2 for calling the ConvBNLayer obj's underlying member method code with example usage: obj.forward(inputs) and returns: y